Immunogenicity of a low-dose diphtheria, tetanus and acellular pertussis combination vaccine with either inactivated or oral polio vaccine compared to standard-dose diphtheria, tetanus, acellular pertussis when used as a pre-school booster in UK children : a 5-year follow-up of a randomised controlled study

This serological follow up study assessed the kinetics of antibody response in children who previously participated in a single centre, open-label, randomised controlled trial of low-dose compared to standard-dose diphtheria booster preschool vaccinations in the United Kingdom (UK). Children had previously been randomised to receive one of three combination vaccines: either a combined adsorbed tetanus, low-dose diphtheria, 5-component acellular pertussis and inactivated polio vaccine (IPV) (Tdap-IPV, Repevax(®); Sanofi Pasteur MSD); a combined adsorbed tetanus, low-dose diphtheria and 5-component acellular pertussis vaccine (Tdap, Covaxis(®); Sanofi Pasteur MSD) given concomitantly with oral polio vaccine (OPV); or a combined adsorbed standard-dose diphtheria, tetanus, 2-component acellular pertussis and IPV (DTap-IPV, Tetravac(®); Sanofi Pasteur MSD). Blood samples for the follow-up study were taken at 1, 3 and 5 years after participation in the original trial (median, 5.07 years of age at year 1), and antibody persistence to each vaccine antigen measured against defined serological thresholds of protection. All participants had evidence of immunity to diphtheria with antitoxin concentrations greater than 0.01IU/mL five years after booster vaccination and 75%, 67% and 79% of children who received Tdap-IPV, Tdap+OPV and DTap-IPV, respectively, had protective antitoxin levels greater than 0.1IU/mL. Long lasting protective immune responses to tetanus and polio antigens were also observed in all groups, though polio responses were lower in the sera of those who received OPV. Low-dose diphtheria vaccines provided comparable protection to the standard-dose vaccine and are suitable for use for pre-school booster vaccination

Systematic infrared image quality improvement using deep learning based techniques

This is the final version. Available from SPIE via the DOI in this recordInfrared thermography (IRT, or thermal video) uses thermographic cameras to detect and record radiation in the longwavelength infrared range of the electromagnetic spectrum. It allows sensing environments beyond the visual perception limitations, and thus has been widely used in many civilian and military applications. Even though current thermal cameras are able to provide high resolution and bit-depth images, there are significant challenges to be addressed in specific applications such as poor contrast, low target signature resolution, etc. This paper addresses quality improvement in IRT images for object recognition. A systematic approach based on image bias correction and deep learning is proposed to increase target signature resolution and optimise the baseline quality of inputs for object recognition. Our main objective is to maximise the useful information on the object to be detected even when the number of pixels on target is adversely small. The experimental results show that our approach can significantly improve target resolution and thus helps making object recognition more efficient in automatic target detection/recognition systems (ATD/R).Centre for Excellence for Sensor and Imaging System (CENSIS)Scottish Funding CouncilDigital Health and Care Institute (DHI)Royal Society of EdinburghNational Science Foundation of Chin

Forecasting in the light of Big Data

Predicting the future state of a system has always been a natural motivation for science and practical applications. Such a topic, beyond its obvious technical and societal relevance, is also interesting from a conceptual point of view. This owes to the fact that forecasting lends itself to two equally radical, yet opposite methodologies. A reductionist one, based on the first principles, and the naive inductivist one, based only on data. This latter view has recently gained some attention in response to the availability of unprecedented amounts of data and increasingly sophisticated algorithmic analytic techniques. The purpose of this note is to assess critically the role of big data in reshaping the key aspects of forecasting and in particular the claim that bigger data leads to better predictions. Drawing on the representative example of weather forecasts we argue that this is not generally the case. We conclude by suggesting that a clever and context-dependent compromise between modelling and quantitative analysis stands out as the best forecasting strategy, as anticipated nearly a century ago by Richardson and von Neumann

Orchestrating Tuple-based Languages

The World Wide Web can be thought of as a global computing architecture supporting the deployment of distributed networked applications. Currently, such applications can be programmed by resorting mainly to two distinct paradigms: one devised for orchestrating distributed services, and the other designed for coordinating distributed (possibly mobile) agents. In this paper, the issue of designing a pro- gramming language aiming at reconciling orchestration and coordination is investigated. Taking as starting point the orchestration calculus Orc and the tuple-based coordination language Klaim, a new formalism is introduced combining concepts and primitives of the original calculi. To demonstrate feasibility and effectiveness of the proposed approach, a prototype implementation of the new formalism is described and it is then used to tackle a case study dealing with a simplified but realistic electronic marketplace, where a number of on-line stores allow client applications to access information about their goods and to place orders

Geospatial information infrastructures

Manual of Digital Earth / Editors: Huadong Guo, Michael F. Goodchild, Alessandro Annoni .- Springer, 2020 .- ISBN: 978-981-32-9915-3Geospatial information infrastructures (GIIs) provide the technological, semantic,organizationalandlegalstructurethatallowforthediscovery,sharing,and use of geospatial information (GI). In this chapter, we introduce the overall concept and surrounding notions such as geographic information systems (GIS) and spatial datainfrastructures(SDI).WeoutlinethehistoryofGIIsintermsoftheorganizational andtechnologicaldevelopmentsaswellasthecurrentstate-of-art,andreflectonsome of the central challenges and possible future trajectories. We focus on the tension betweenincreasedneedsforstandardizationandtheever-acceleratingtechnological changes. We conclude that GIIs evolved as a strong underpinning contribution to implementation of the Digital Earth vision. In the future, these infrastructures are challengedtobecomeflexibleandrobustenoughtoabsorbandembracetechnological transformationsandtheaccompanyingsocietalandorganizationalimplications.With this contribution, we present the reader a comprehensive overview of the field and a solid basis for reflections about future developments

Alloy surface segregation in reactive environments: A first-principles atomistic thermodynamics study of Ag3Pd(111) in oxygen atmospheres

We present a first-principles atomistic thermodynamics framework to describe the structure, composition and segregation profile of an alloy surface in contact with a (reactive) environment. The method is illustrated with the application to a Ag3Pd(111) surface in an oxygen atmosphere, and we analyze trends in segregation, adsorption and surface free energies. We observe a wide range of oxygen adsorption energies on the various alloy surface configurations, including binding that is stronger than on a Pd(111) surface and weaker than that on a Ag(111) surface. This and the consideration of even small amounts of non-stoichiometries in the ordered bulk alloy are found to be crucial to accurately model the Pd surface segregation occurring in increasingly O-rich gas phases.Comment: 13 pages including 6 figures; related publications can be found at http://www.fhi-berlin.mpg.de/th/th.htm

Relaxation in the glass-former acetyl salicylic acid studied by deuteron magnetic resonance and dielectric spectroscopy

Supercooled liquid and glassy acetyl salicylic acid was studied using dielectric spectroscopy and deuteron relaxometry in a wide temperature range. The supercooled liquid is characterized by major deviations from thermally activated behavior. In the glass the secondary relaxation exhibits the typical features of a Johari-Goldstein process. Via measurements of spin-lattice relaxation times the selectively deuterated methyl group was used as a sensitive probe of its local environments. There is a large difference in the mean activation energy in the glass with respect to that in crystalline acetyl salicylic acid. This can be understood by taking into account the broad energy barrier distribution in the glass.Comment: 8 pages, 3 figures, Submitted to Phys. Rev.

Steam reforming on transition-metal carbides from density-functional theory

A screening study of the steam reforming reaction (CH_4 + H_2O -> CO + 3H_2) on early transition-metal carbides (TMC's) is performed by means of density-functional theory calculations. The set of considered surfaces includes the alpha-Mo_2C(100) surfaces, the low-index (111) and (100) surfaces of TiC, VC, and delta-MoC, and the oxygenated alpha-Mo_2C(100) and TMC(111) surfaces. It is found that carbides provide a wide spectrum of reactivities towards the steam reforming reaction, from too reactive via suitable to too inert. The reactivity is discussed in terms of the electronic structure of the clean surfaces. Two surfaces, the delta-MoC(100) and the oxygen passivated alpha-Mo_2C(100) surfaces, are identified as promising steam reforming catalysts. These findings suggest that carbides provide a playground for reactivity tuning, comparable to the one for pure metals.Comment: 6 pages, 4 figure

Roadmaps to Utopia: Tales of the Smart City

Notions of the Smart City are pervasive in urban development discourses. Various frameworks for the development of smart cities, often conceptualized as roadmaps, make a number of implicit claims about how smart city projects proceed but the legitimacy of those claims is unclear. This paper begins to address this gap in knowledge. We explore the development of a smart transport application, MotionMap, in the context of a £16M smart city programme taking place in Milton Keynes, UK. We examine how the idealized smart city narrative was locally inflected, and discuss the differences between the narrative and the processes and outcomes observed in Milton Keynes. The research shows that the vision of data-driven efficiency outlined in the roadmaps is not universally compelling, and that different approaches to the sensing and optimization of urban flows have potential for empowering or disempowering different actors. Roadmaps tend to emphasize the importance of delivering quick practical results. However, the benefits observed in Milton Keynes did not come from quick technical fixes but from a smart city narrative that reinforced existing city branding, mobilizing a growing network of actors towards the development of a smart region. Further research is needed to investigate this and other smart city developments, the significance of different smart city narratives, and how power relationships are reinforced and constructed through them